• Title:Big Book of R
• Author(s): Oscar Baruffa
• Publisher: Self Publishing (2024-12-07); eBook (Creative Commons Licensed)
• License(s): Creative Commons License (CC)
• Paperback: N/A
• eBook: HTML
• Language: English
• ISBN-10: N/A
• ISBN-13: N/A
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Book Description

This book covers a wide range of topics in a single volume, including big data, databases, statistical machine learning, data wrangling, data visualization, and the reporting of results.

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• Amazon

• The R Programming Language
• Statistics, and SAS Programming
• Data Analysis and Data Mining

• Big Book of R (Oscar Baruffa)
• The Mirror Site (1) - ePub

• Hands-On Programming with R: Functions and Simulations

  This book not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You’ll gain valuable programming skills and support your work as a data scientist at the same time.

• Mastering Software Development in R (Roger D. Peng, et al.)

  The book covers R software development for building data science tools. As the field of data science evolves, it has become clear that software development skills are essential for producing useful data science results and products.

• Efficient R Programming: Practical Guide to Smarter Programming

  This book is about increasing the amount of work you can do with R in a given amount of time. It's about both computational and programmer efficiency. This book is for anyone who wants to make their use of R more reproducible, scalable, and faster.

• Cookbook for R: Best R Programming TIPs (Winston Chang)

  The goal of this cookbook is to provide solutions to common tasks and problems in analyzing data. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.

• R Graphics Cookbook: Practical Recipes for Visualizing Data

  This cookbook provides more than 150 recipes to help scientists, engineers, programmers, and data analysts generate high-quality graphs quickly - without having to comb through all the details of R's graphing systems.

• An Introduction to R (Alex Douglas, et al.)

  The main aim of this book is to help you climb the initial learning curve and provide you with the basic skills and experience (and confidence!) to enable you to further your experience in using R.

• R Packages: Organize, Test, Document, and Share Your Code

  Turn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author's package development philosophy.

• Advanced R (Florian Prive)

  This book aims at giving a wide understanding of many aspects of R. Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R's functionality.

• Advanced R, Second Edition (Hadley Wickham)

  This book helps you understand how R works at a fundamental level. Designed for R programmers who want to deepen their understanding of the language, and programmers experienced in other languages to understand what makes R different and special.

• Advanced R Solutions (Malte Grosser, et al)

  This book offers solutions to the exercises from Advanced R, 2nd Edition by Hadley Wickham. It is work in progress and under active development. The 2nd edition of Advanced R is in print now and we hope to provide most of the answers.

• R for Data Science: Visualize, Model, Transform, Tidy, Import

  This book teaches you how to do data science with R: You'll learn how to get your data into R, get it into the most useful structure, transform it, visualize it and model it, how data science can help you work with the uncertainty and capture the opportunities.